Autofocusing of in-line holography based on compressive sensing

被引:23
|
作者
Zhang, Yiyi [1 ]
Huang, Zhengzhong [2 ]
Jin, Shangzhong [1 ]
Cao, Liangcai [2 ]
机构
[1] China Jiliang Univ, Coll Opt & Elect Technol, Hangzhou 310018, Zhejiang, Peoples R China
[2] Tsinghua Univ, Dept Precis Instrument, State Key Lab Precis Measurement Technol & Instru, Beijing 100084, Peoples R China
关键词
Holographic reconstruction; Compressive sensing; Autofocusing; Twin-image-free; DIGITAL HOLOGRAPHY; PHASE-RETRIEVAL; OFF-AXIS; RECONSTRUCTION; MICROSCOPY; CRITERION; OBJECTS;
D O I
10.1016/j.optlaseng.2021.106678
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Holographic reconstruction is affected by the phase-conjugate wave arising from the symmetry of the complex field. Compressive sensing (CS) has been used in in-line digital holography (DH) to eliminate noise, especially the interference from twin images. Herein, CS with total variation regularization combining autofocusing is presented. It provides an autofocusing function from a single-exposure hologram and obtains reconstructed objects without twin image noise. A series of images at a fixed interval within a reconstruction distance are processed using a two-step iterative shrinkage/thresholding algorithm in CS. It can calculate the focus distance in a larger range around the focal plane using twin-image-free reconstruction, so it can achieve a higher focusing accuracy than traditional focusing methods, including the Laplace operator, absolute gradient operator, and Tamura coefficient. The proposed method is a simple combination of algorithms and a powerful extension that can effectively improve simulated and experimental image quality and handle difficult datasets, which existing algorithms cannot.
引用
收藏
页数:7
相关论文
共 50 条
  • [41] Autofocusing in Digital Holography
    Ilhan, Hazar A.
    Dogar, Mert
    Ozcan, Meric
    PRACTICAL HOLOGRAPHY XXVII: MATERIALS AND APPLICATIONS, 2013, 8644
  • [42] Parameter estimation of single cloud particle based on in-line digital holography
    Li, Baosheng
    Ma, Fei
    Huang, Meng
    SELECTED PAPERS OF THE PHOTOELECTRONIC TECHNOLOGY COMMITTEE CONFERENCES, 2015, 9795
  • [43] Autofocusing in digital holography based on an adaptive genetic algorithm
    Wang, Zhongyang
    Ma, Hongwei
    Chen, Yuan
    Liu, Dengxue
    JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2024, 41 (06) : 976 - 987
  • [44] Recovering the size of nanoparticles by digital in-line holography
    Pejchang, Darawan
    Coetmellec, Sebastien
    Grehan, Gerard
    Brunel, Mare
    Lebrun, Denis
    Chaari, Anis
    Grosges, Thomas
    Barchiesi, Dominique
    OPTICS EXPRESS, 2015, 23 (14): : 18351 - 18360
  • [45] Randomness assisted in-line holography with deep learning
    Manisha, Aditya Chandra
    Mandal, Aditya Chandra
    Rathor, Mohit
    Zalevsky, Zeev
    Singh, Rakesh Kumar
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [46] Randomness assisted in-line holography with deep learning
    Aditya Chandra Manisha
    Mohit Mandal
    Zeev Rathor
    Rakesh Kumar Zalevsky
    Scientific Reports, 13
  • [47] INTRINSIC SPECKLE NOISE IN IN-LINE PARTICLE HOLOGRAPHY
    MENG, H
    ANDERSON, WL
    HUSSAIN, F
    LIU, DD
    JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 1993, 10 (09): : 2046 - 2058
  • [48] In-line digital holography with double knife edge
    Ramirez, Claudio
    Iemmi, Claudio
    Campos, Juan
    MODELING ASPECTS IN OPTICAL METROLOGY V, 2015, 9526
  • [49] Phase retrieval methods in in-line digital holography
    Rong, Lu
    Wang, Dayong
    Wang, Yunxin
    Huang, Haochong
    Zhongguo Jiguang/Chinese Journal of Lasers, 2014, 41 (02):
  • [50] Twin-image-free compressive holography with autofocusing from single subsampled hologram
    Zhang, Cheng
    Zhou, Jiaxuan
    Wu, Feng
    Wei, Sui
    PHYSICA SCRIPTA, 2023, 98 (07)